Fractional Online Learning Rate: Influence of Psychological Factors on Learning Acquisition.

IF 0.6 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Aldo Ramirez-Arellano, Jose Maria Sigarreta Almira, Juan Bory Reyes
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Abstract

The quantification of learning acquisition in a blended and online course is still slightly explored from the complex systems lens. The fractional online learning rate (fOLR) using fractional integrals is introduced. The notion of fOLR is based on the nonlinearity of the individual students learning pathway network, built from Learning Management System log files. Several learning pathway networks from students that pass or fail the course were constructed. The Akaike information criterion shows that the minimum number of boxes to cover these networks follow a power-law model. Further analysis shows that the fOLR model and its parameters were significantly compared with the online learning rate model. Thus, the fOLR was computing power and delayed power models, inspired by the "law of practice." The results show that the fractional definition is a better model and has a nonlinear relationship with the overall grade. Also, engagement and disengagement mould the fOLR curve. It means that the student's performance is affected by the engagement, and it is necessary that they are encouraged to pay more effort and attention to the learning activities, and those activities need to be designed to be fun and pleasant to improve the learning achievements.

分数在线学习率:心理因素对学习习得的影响。
从复杂系统的角度来看,混合在线课程中学习习得的量化仍有待探索。介绍了基于分数阶积分的分数阶在线学习率。fOLR的概念是基于个体学生学习路径网络的非线性,建立在学习管理系统日志文件上。通过或不通过课程的学生构建了几个学习途径网络。赤池信息准则表明,覆盖这些网络的最小盒数遵循幂律模型。进一步分析表明,fOLR模型及其参数与在线学习率模型具有显著性差异。因此,fOLR是计算能力和延迟能力模型,受到“实践法则”的启发。结果表明,分数定义是一个较好的模型,并与整体等级呈非线性关系。此外,接触和脱离接触塑造了fOLR曲线。这意味着学生的表现受到参与的影响,需要鼓励他们在学习活动中付出更多的努力和关注,这些活动需要设计得有趣和愉快,以提高学习成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
11.10%
发文量
26
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